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Algorithms from and for Nature and Life pp 439–447Cite as

Lifestyle Segmentation Based on Contents of Uploaded Images Versus Ratings of Items

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Abstract

Clustering algorithms are standard tools for marketing purposes. So, e.g., in market segmentation, they are applied to derive homogeneous customer groups. However, recently, the available resources for this purpose have extended. So, e.g., in social networks potential customers provide images which reflect their activities, interests, and opinions. To compare whether contents of uploaded images lead to similar lifestyle segmentations as ratings of items, a comparison study was conducted among 478 people. In this paper we discuss the results of this study that suggests that similar lifestyle segmentations can be found. We discuss advantages and disadvantages of the new approach to lifestyle segmentation.

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Acknowledgements

This research is funded by Federal Ministry for Education and Research under grants 03FO3072. The author is responsible for the content of this paper.

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Authors and Affiliations

  1. Institute of Business Administration and Economics, Brandenburg University of Technology Cottbus, 03013, Cottbus, Germany

    Ines Daniel & Daniel Baier

Authors
  1. Ines Daniel
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  2. Daniel Baier
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Correspondence to Ines Daniel .

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Editors and Affiliations

  1. University of Essex Department of Mathematical Sciences, Colchester, United Kingdom

    Berthold Lausen

  2. Ghent University Department of Marketing, Ghent, Belgium

    Dirk Van den Poel

  3. University of Marburg Databionics, FB 12, Marburg, Germany

    Alfred Ultsch

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Daniel, I., Baier, D. (2013). Lifestyle Segmentation Based on Contents of Uploaded Images Versus Ratings of Items. In: Lausen, B., Van den Poel, D., Ultsch, A. (eds) Algorithms from and for Nature and Life. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-00035-0_44

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